55 citations · 58 across the 12 of their papers we have counts for
7 papers · 1 filter
BOOKMARKS: Efficient Active Storyline Memory for Role-playing
Letian Peng, Ziche Liu, Yiming Huang +4
Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling) mainly rely on incremental s…
Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis
Xinkai Zou, Yiming Huang, Zhuohang Wu +5
Simulating how organized groups (e.g., corporations) make decisions (e.g., responding to a competitor's move) is essential for understanding real-world dynamics and could benefit r…
Seeing is Coding: On the Effectiveness of Vision Language Models in Code Understanding
Yuling Shi, Chaoxiang Xie, Zhensu Sun +7
Large Language Models (LLMs) have achieved remarkable success in source code understanding, yet as software systems grow in scale, computational efficiency has become a critical bo…
Deriving Character Logic from Storyline as Codified Decision Trees
Letian Peng, Kun Zhou, Longfei Yun +2
Role-playing (RP) agents rely on behavioral profiles to act consistently across diverse narrative contexts, yet existing profiles are largely unstructured, non-executable, and weak…
Codified Foreshadowing-Payoff Text Generation
Longfei Yun, Kun Zhou, Yupeng Hou +2
Foreshadowing and payoff are ubiquitous narrative devices through which authors introduce commitments early in a story and resolve them through concrete, observable outcomes. Howev…
The Price of Format: Diversity Collapse in LLMs
Longfei Yun, Chenyang An, Zilong Wang +2
Instruction-tuned large language models (LLMs) employ structured templates, such as role markers and special tokens, to enforce format consistency during inference. However, we ide…
UltraGen: Extremely Fine-grained Controllable Generation via Attribute Reconstruction and Global Preference Optimization
Longfei Yun, Letian Peng, Jingbo Shang
Fine granularity is an essential requirement for controllable text generation, which has seen rapid growth with the ability of LLMs. However, existing methods focus mainly on a sma…